The purpose of this paper is to predict the mechanical properties of galvanized steel, using appropriate data mining techniques such as neural network, support vector machine, regression analysis and regression tree methods. It is found that by using the neural network technique one can get the best result for predicting the mechanical properties of galvanized steel according to the values of input parameters and also considering the effects of annealing temperature and line speed as the controlling parameters
Raw data and processed data used in the paper "A predicting model for properties of steel using the ...
AbstractThe paper proposes an approach to the design of the chemical composition of steel, which is ...
The article presents opportunities offered by the data mining analysis as applied to studies of the ...
In this paper, the application of data mining and artificial intelligence techniques stemming from o...
Zinc is used widely as a corrosion resistant coating on steel. However, in Europe, zinc is considere...
The mechanical properties of the SAPH440 hot rolled steel sheet are mainly controlled to satisfy pro...
The paper presents a machine learning-based system aimed at improving the homogeneity of tensile pro...
The article presents a computational model build with the use of artificial neural networks optimize...
One of the fields where it is possible to exploit neural networks is predicting the mechanical prope...
This paper deals with mechanical properties of galvannealed automotive steel sheet. The composition ...
V diplomskem delu smo predstavili povezavo med dvema različnima področjema, in sicer umetnimi nevron...
This paper presents the results obtained using Machine Learning (ML) algorithms to predict the mecha...
The annealing process is one of the important operations in production of cold rolled steel sheets, ...
The paper presents a model for predicting the machinability of steels using the method of artificial...
This study explores the use of machine learning (ML) as a data-driven approach to estimate hot ducti...
Raw data and processed data used in the paper "A predicting model for properties of steel using the ...
AbstractThe paper proposes an approach to the design of the chemical composition of steel, which is ...
The article presents opportunities offered by the data mining analysis as applied to studies of the ...
In this paper, the application of data mining and artificial intelligence techniques stemming from o...
Zinc is used widely as a corrosion resistant coating on steel. However, in Europe, zinc is considere...
The mechanical properties of the SAPH440 hot rolled steel sheet are mainly controlled to satisfy pro...
The paper presents a machine learning-based system aimed at improving the homogeneity of tensile pro...
The article presents a computational model build with the use of artificial neural networks optimize...
One of the fields where it is possible to exploit neural networks is predicting the mechanical prope...
This paper deals with mechanical properties of galvannealed automotive steel sheet. The composition ...
V diplomskem delu smo predstavili povezavo med dvema različnima področjema, in sicer umetnimi nevron...
This paper presents the results obtained using Machine Learning (ML) algorithms to predict the mecha...
The annealing process is one of the important operations in production of cold rolled steel sheets, ...
The paper presents a model for predicting the machinability of steels using the method of artificial...
This study explores the use of machine learning (ML) as a data-driven approach to estimate hot ducti...
Raw data and processed data used in the paper "A predicting model for properties of steel using the ...
AbstractThe paper proposes an approach to the design of the chemical composition of steel, which is ...
The article presents opportunities offered by the data mining analysis as applied to studies of the ...